[In a collaborative co-writing effort originally appearing on RecruitingDaily, Derek Zeller and I took turns writing paragraphs. If you want to learn more about either of us, use google, bing, etc.. That’s your job after all.]

My first name is not passive; it’s not Talent. My Mom never gave birth to a child named Candidate; my Dad never told his friends, “This is my son, Human Capital.”

My Name Is…

My name is Monica, and I am frightened. I am a single mother trying to raise a family and protect them.I am diligent, trustworthy, and I will make a company better. My name is Monica, and all I ask is a chance, an opportunity to at least talk with you for just a moment, all I want is an opportunity to prove myself. My name is Monica, I don’t want a handout. I want to work to provide for my family, feed my children, and pay my rent. Please take a chance on me, I promise you will not be disappointed Please? My name is Monica, and I am scared. Why?

My Name Is…

My name is Emory, and I am angry. After working for the same damn company for 36 years and consistently receiving great reviews and raises, all of a sudden my job gets outsourced to some third world country and I’m not even given a chance to interview for another internal job? What we’re going in a different direction is the BS line the consultant tried to feed me; HR didn’t even have the guts to tell me this to my face. What am I supposed to do now? Drive for Uber? How am I going to pay for my kids’ college tuitions? Who’s going to hire someone who isn’t an anointed Millennial with skills that are “up to date”? Hell, when did using a smartphone app become more important than being able to build a smartphone? What’s wrong with these people? Don’t they know that they’re destroying our country? Why I wasn’t even asked to stay? Why?

My Name Is…

My name is Carl, and I am tired. I am over 40 in Silicon Valley and I am sick of hearing that I am not a culture fit for your company. I am over qualified for the position. Since when did actually having the skills to do what is required to get that project done be a bad thing? Why are all the startups ignoring me, blatantly telling me that I am too old? I have shaved off my beard, dyed my hair, I’ve been there and done that and got the requisite t-shirt. Why do you have a team trying to accomplish a project I could do alone and before the deadline? The reason you are going under is that you are hiring friends and pretty people instead of those who know how to get the job done. You choose to fail without me instead of succeeding with me. Why?

My Name Is…

My name is Samantha, and I am so confused. Everything I’ve always wanted to achieve I have. While I was in school, I took some of the hardest courses. I volunteered in my community. I tutored high school girls. I have a high GPA. And all I can get is a job as a Receptionist while living with three other girls in Brooklyn? Look, I know we’ve been called the entitled generation but when did wanting to make a difference in the world come to mean entitled to a job that has nothing to do with your major and falling further and further behind on your bills? Why don’t you just ask me to help you and your company to be better? You’re not that much older than me yet you already know that I won’t be able to do the job? Why are you so afraid to take a chance on me? Why?

My Name Is…

My name is Hector and I am lost in understanding. At eighteen, I joined the US Marines because I could not afford college and I wanted to serve my country and I am proud that I did. I fought in two wars. I took a bullet for this Nation only to come home to nothing. To be forgotten. I am told that I could pose a possible disturbance due to PTSD, which I don’t have. I can not get a position anywhere, not even Walmart as a stocker. I carried out logistical missions, drove million dollar machinery and led men into battle when I had to. Yet here I am, one month away from being homeless because I cannot afford rent. My savings are almost gone, and all I find is stone hearted people that callously never return my calls or emails after they first talk to me. Why?

Our Names Are…

Our names are Derek and Steve, and we don’t know what to say to these people. They are people you know – those resumes you’re holding. Not sure when we forgot that but we’re still left speechless by the outcome. These resumes aren’t the whole story for people who have names and lives – stories to tell and experiences that could change your company.

Many years ago, we began our journey into this profession and have helped so many people get something better. There have been struggles, sure, many whom we could not help or those we didn’t want to due to arrogance. Yet what is worse is the lack of support we receive from the bulk of those in our recruiting community.

Far too many recruiters don’t practice the listening skills they’re seeking and make too many assumptions regarding what they believe you want to do, what they believe will make you happy. Far too many recruiters – seasoned and non-seasoned alike – believe they have ESP and are experienced psychotherapists. Damned what you say during a screen or an interview, they’ve already made up their feeble minds.

Too many recruiters practice the “fake it until you make it” training model, and actually believe they’re skilled enough to assess people’s functional and technical skills. Many won’t even admit they don’t know what they don’t know.

Feedback. None. They will even tell boldface lies to your face.

Lying, faking, and silence might be major pillars of a tawdry drama–romance–crime novel but in our profession, these three elements lead to only one thing:

Like this:

For 15 Septembers I have felt the angst in the days leading up to 9/11 and on the day, to wake up with tears that made the first steps out of bed difficult. I’ve been so fortunate to be allowed to spend each 9/11 at Squad 1 and get to know the firefighters and their families (today we talked about ink and gushed over each other’s tats); to be able to hear Metrotech’s announcements for when the Towers fell; to be at the Mass around the corner from the firehouse.

I’ve also seen the faces of spouses, siblings, relatives and parents of the departed grow weary and weathered with grief that I suspect will never go away. No one who lost someone can ever forget.

Last year, the Washington Post published a somewhat objective assessment on how many Americans actually remember 9/11.With each passing year, more Americans are born whose only understanding of the terrorist attacks will come via stories handed down by older friends and family, or taught in a social studies class (and this teaching comes before revisionist educators choose to change the details to be more inclusive of terrorists groups).

WaPo’s analysis showed that on 9/11/2015, 25.8% of the country was six years of age and younger (8%), or not yet born (17.8%). With approximately 4 million people being born each year and approximately 2.6 million dying each year, the percentage of people being born after 9/11 will rise every year, memories of others will change or fade, and the life stories of specific people will likely be blended together into an amorphous mass that is transformed into “an event in United States history.”

Just like the day the Japanese attacked Pearl Harbor on December 9, 1941, “a day which will live in infamy.” Except that only 6.2% of Americans still have a personal recollection of the event. Most Americans don’t know who uttered those infamous seven words. That 2,402 people were killed in the attacks. Or that one day later, the United States formerly entered World War II.

2,996 people were murdered on 9/11. Here in New York City, of the 2,753 people killed that day, only 1,638 people have been forensically identified. Do and math and ponder the significance of someone you love dying and literally disappearing forever.

And the cancerous dust will likely produce a higher number of deaths than the initial attacks…

According to the CDC and OSHA, as of July 2016, 1,064 rescue and recovery workers have died from diseases directly attributed the attack; there will be more. Even after the dust settled, 9/11 continued to be a witch’s brew of death. Compared to pre 9/11 data, FDNY cancer rates are 19% to 30% percent higher for firefighters who worked on the pile.

But remembering 9/11 is more than just big data; it’s about the people whose stories might never be truly known when the events of the day are distilled into history lessons…

My friend, fellow Jones Beach Lifeguard, NYC Firefighter with Squad 1, and rowing partner Dave Fontana was in the South Tower; my fellow Jones Beach Lifeguard Billy Burke – who always answered the telephone, “Lifeguards, Robert Moses State Park Field Three. William F. Burke, Junior speaking. How can I help you?” – was in the North Tower with his 21 Engine crew.

9/11 was also Dave’s 8th wedding anniversary (I’ll do some math – today would have been his and Marian’s 23rd anniversary); they were to have celebrated their anniversary at the Central Park Boathouse and at the Whitney Museum. Some time around 9AM, he called his wife as he was finishing his 24 at Squad 1 and told her, “I’ll meet you in 10 minutes.” Then Hell on Earth began. Dave and his other Squad brothers were partially through the Brooklyn Battery Tunnel when traffic snarled; they ran the rest of the way to the Towers (that’s 60 pounds of gear).

Dave’s last known location was on the 45th Floor. His memorial service was held on October 17, 2001 – without a body. His body was found on December 8, 2001. There was another and far more private funeral shortly thereafter.

Billy, the Captain of 21 Engine, was in the North Tower with his crew as the South Tower fell. His crew kept calling, “We got to get out, Cap.” His answer?

“You guys go ahead; we’ll meet at the rig.”

Billy disappeared to search another floor, while his crew made it out before the North Tower also collapsed. His body has never been found. How can I help?By giving up your life and saving the lives of others.

Ashes to ashes, dust to dust.

While history lessons about 9/11 will eventually be written with the insensitivity of numbers, 9/11 is really a lesson about souls lost and lives sent in unexpected directions. Whose stories will you tell? Will you know how Dave and Billy truly lived? How about my fellow Jones Beach lifeguards Christian Maltby and Tom Palazzo who worked at Cantor Fitzgerald? Will you care that they walked this planet and touched so many?

15 Septembers later and it still feels like a deep paper cut to the soul. But at least I’m here; I still have time to think and act in ways that would make Dave, Billy, Chris, and Tommy proud. So ask me about them, and I’ll sit with you for as long as wish.

I want to tell you their stories so 9/11 becomes an historical event about the lives and souls of remarkable people and not one of distilled data.

Like this:

Recruiting industry analyst Rob McIntosh believes “AI recruiting” is the future of recruiting. Ah, another future of recruiting article! Another tome in the latest assembly line of predictions that the profession will be elevated to the one where Supreme Bot Beings sit atop the Totem of Talent. Alas, being a human recruiter is no longer considered to be sexy enough for the Futurists.

Actually, automated recruiting isn’t what Rob is about, efficient recruiting is. We’ll get back to this notion in a few paragraphs.

It is very easy to be snookered in by the sweet smell of technology, unicorn valuations, 30 under 30 lists – and anything that comes to the masses via Google. But allow me to offer another perspective to this future of recruiting discussion.

Artificial Stupidity

If there’s artificial intelligence, then by logic there has to be artificial stupidity – as in taking the Word of the Bot as Gospel. People, this is a very slippery slope that portends to push aside human expertise, experience, and compassion. Sure, the system can learn, the AlphaGo architecture is a unique extension of previous AI architectures (more about this soon), but humans have a funny way of turning logic on its side and playing a hunch that has a deeper, more robust meaning than any Monte Carlo tree search fueled by “…a huge amount of compute power” can make. Again, more about this later.

Just to be clear, I’m not against #BotRecruiting for the repeatable, scalable types of roles that take up so much of a Sourcer’s or Recruiter’s time, with or without pipelines and talent communities. Just the opposite, I’m very bullish on #AIrecruiting, addressing 68% of all hiring that isn’t significantly specialized (this is the plus or minus one standard deviation of all roles) based upon the range of problems to be solved when on the job.

I’m talking about large-scale hiring in, for instance, customer service, early career sales, retail, warehousing, even entry-level software development, where data is plenty, efficiency is a key goal, and humans are susceptible to injecting bias into the hiring process. I’m also bullish about an #AIrecruiting system that cultivates the digital crumbs and creates “probabilities of behavior” that can be used by human recruiters at some point in the process. We’re getting there tech-wise, but have a long way to move beyond black and white stones.

As promised earlier, one thing that Rob missed out on was describing AlphaGo’s architecture (it’s a darn good read), and why its performance is more evolved than previous attempts at building artificial intelligence solutions to games:

“…it combines a state-of-the-art tree search with two deep neural networks, each of which contains many layers with millions of neuron-like connections. One neural network, the “policy network”, predicts the next move, and is used to narrow the search to consider only the moves most likely to lead to a win. The other neural network, the “value network”, is then used to reduce the depth of the search tree — estimating the winner in each position in place of searching all the way to the end of the game.”

See what AlphaGo is doing with the parallel networks? Assessing hunches…feelings…ESP is what many recruiters call it. With experience, our hunches, fueled by many different scenarios and outcomes from the past, produce a higher probability of the likelihood of success, and with some hunches we learn that they don’t produce a desired outcome. Same with AlphaGo, as long as there’s more computing power to drive the parallel nature of the algorithm.

“Of course, all of this requires a huge amount of compute power, so we made extensive use ofGoogle Cloud Platform, which enables researchers working on AI and Machine Learning to access elastic compute, storage and networking capacity on demand. In addition, new open source libraries for numerical computation using data flow graphs, such as TensorFlow, allow researchers to efficiently deploy the computation needed for deep learning algorithms across multiple CPUs or GPUs”

Let me put this another way: Remember the post-mortem analysis of meteorologists who had tried to predict the path of Hurricane Sandy? The picture below details all the models of possible paths based on a tremendous amount of data collected over decades. These models were created using a variety of simulations running on some of the most brutish computers on the planet. Yet we remember what happened, and the cost? Simulations and predictions are just that.

Each “Hurricane Sandy” adds more data and new sets of rules (learning) that enrich the model and change the hunches. Yet we all know that even the best model results in catastrophic damages. Sometimes the recruiting and hiring of the right person truly is a confluence of hunches, to an experienced recruiter, almost leaps of faith. This #AIrecruiting sure isn’t easy.

“One thing I’m seeing among my own faculty is the realization that we, technologists, computer scientists, engineers who are building AI, have to appeal to someone else to create these programs. When coming up with a driverless car, for example, how does the car decide what to do when an animal comes into the road? When you write the code there’s the question: How much is an animal’s life worth next to a human’s life? Is one human life worth the lives of a billion domestic cats? A million? A thousand? I would hate to be the person writing that code.”

Consider the #AIrecruiting software developer, if they are an avowed animal lover, do they play a Death Race 2000 scenario in their head while coding? This is one of many issues with developing systems to replace or augment humans.

Open source, open stack, and APIs too often mask the fact that there are human beings on the other side of the application. Artificial intelligence, machine learning, intelligence systems, and automation so good that they’ll replace human beings, are not by themselves the seeds of success but are foods that when consumed unchecked further the divide between people and technology. The carrot that is held in front of us, that will have more time to do the things we love, isn’t necessarily reality. Just like the addictiveness of drugs, alcohol, and cigarettes, technology draw us in and not let go. Ask me how often I’m hiking on a lonesome trail only to come across people glued to their smartphones.

More data does not mean necessarily translate into better decisions when the human brain is conditioned to trust the technology rather than the brain.

Perfect marriages end in divorce: what’s going to happen when all these perfect Bot selected people begin working with other perfect Bot selected people and one of them farts in a meeting? Or selects “Reply All” with an unfortunate joke? Or votes for Trump/Bernie/Clinton and posts it for the world to see? Or has sex with a co-worker on their desk, then breaks up with them the next week leading to a barrage of social media stupidity? Will the “person” who pushed these Bot hires through be dinged for a bad hire? Or will the #AIrecruiting system be forced to take a timeout?

Back to the use of AI in recruiting: the question to ask is what do we not do especially well right now? Let’s, as a profession, talk now about the rules that govern these tasks and continue to tune them until we reach consensus on best practices. Let’s decide upon where automation in recruiting makes sense for the people who are likely to be impacted by automation.

‘Yes, let’s put more human back into recruiting.’CLICK TO TWEETThe journey from predicting the movement of black and white stones to the behavior of people replete with an unending number of human variables is a huge responsibility for our profession. Rather than get all worked up over a technology to replace people, think about how #AIrecruiting can serve to re-focus organizations on how important recruiting should be, to not only the solvency of companies but to the lives of the people we touch. It is the ethical thing for us to do.

Let’s end this tome with the last line of Aldous Huxley’s Brave New World – a fitting be careful what you wish for rejoinder to what happens when you implicitly trust technology:

“Slowly, very slowly, like two unhurried compass needles, the feet turned towards the right; north, north-east, east, south-east, south, south-south-west; then paused, and, after a few seconds, turned as unhurriedly back towards the left. South-south-west, south, south-east, east…”

Like this:

We didn’t turn it on, but we can’t turn it off, off, offSometimes I wonder how did we get hereIt seems like all we ever hear is – Noise ~Kenny Chesney

Lately, there’s been a growing amount of anger, disillusionment, and Straight-Outta-Compton need for attention across the social galaxy. Lines being drawn, lines being crossed, lines being blurred and the silence or screams that have followed have been too easy to track – I mean, if you wanted to spend hours each day involved in this “social sleuthing”. Many of us looked at what was going on like the car wreck on the side of the road, slowing down to rubberneck at the carnage. Our collective minds have been overwhelmed by the Comments, with the unfounded accusations, and the downright malicious behavior.

Folks, the time is now for an industry-wide wake-up call. YES, we contribute to the stench just like everyone, but we try to provide something positive, something we see as having value. Whether others believe we do, or how this “value” is perceived, is going to be up to the reader’s interpretation.

Words are supremely powerful and when used poorly, can emotionally hurt even the most hardened of people. Here is the thing: it’s not necessary nor productive to let your Id run wild on social media when the Super Ego knows there are better ways to make your point. You are not a Captain of anything when seated by a computer espousing some drivel or spewing hatred. There’s no positive outcome for ever joining the Contagion Crew, taking sides, and verbally ganging up on others – just as there’s no reason for fomenting a fight because you get a rise out of watching people froth at the mouth.

Grow up!

There is a laundry room in your house or down the street. We, as in the majority of people online, are not interested in your laundry, dirty or clean. How many of you remember high school? We do, and while it wasn’t awful, it was full of things we were glad to leave behind. Backstabbing, cliques, and gossiping were part of many a social circle back then before there was anything as intimidating as social media. We all went our ways and thank goodness there weren’t going to be any more cool kids.

Except, apparently, there still are those that don’t agree.

We see it coming back, rearing its ugly head in the professional world, and to say it’s a shock to the system is an understatement. And it’s marked deviation from the drama back in the day.

Back then, if you had an issue with someone, the confrontation had to be handled face-to-face. If you needed to avoid the drama, hiding out in your house was an option. Most importantly, you weren’t sharing this spectacle with 1100 of your closest – cue hand air quotes – friends.

Social Media has decisively changed the game as it relates to how people handle drama in their personal and professional lives. When you lump in the fact that those two lines are blurred within these relationships that are created as a result of social media, it compounds things. Sadly, this type of relationship development is commonplace in recruiting.

Think of all the conferences that aren’t weird to go to now, because you’ve been interacting with ‘Sally’ who recruits for ACME for two years, and now you’re meeting at a {insert conference here} for the first time in real life. Many of us have developed the relationships that we have because we find commonality with colleagues on both levels. We suspect this is not unique to the recruiting industry, but hey, you write about what you know. What this means is that within our industry the family tree runs in both directions – often with less than pleasing results.

Handling your business with someone used to take some cojonés. Nowadays, it takes nothing to throw jabs through your WordPress site or to add a dash of snark to your posts on Facebook and Twitter. And because the Ego is a fickle fellow, many of these barbs will be served back and forth at breakneck speed and reckless abandon without regard for the people caught in the crossfire – which amounts to all of us bearing digital witness to this. Remember kids, what you say online stays online and as Levy espouses, will follow you to the grave.

For sure, there will be the clogging of News Feeds, and the endless string of comments on Facebook (especially since the posts will be strategically placed in groups where it will get eyeballs of varying temperaments, with responses ranging from meh to unbridled outrage). However beyond the digital shooting gallery, there are the conflicts between colleagues as humans and friends. Are people expected to choose to side with one person or the other? Are you on Team Sally or Team John? Aren’t these conundrums we left in the dust with Cavriccis and Scunciis? (sorry two of us grew up on Long Island, an Area-51-like testing ground for horrible fashion trends). We’re supposed to be older and wiser, or so the legends tell us. But yet, we as seasoned professionals are still mired in immature discourse. Heaven help us if there’s something about Social Media that inherently pushes our EQ back to our early teenage years…

We collectively struggle with the impetus for all of this (besides the ever-present Ego and it’s new social behavior known as humblebragging), and how it has become so pervasive. Don’t we all want to see each other succeed? Whether you are in on Team Recruiting, Team Branding, Team Content or Team HRTech, don’t we all stand to gain from the success of others in our industry? Even if you aren’t a fangirl of the work that person is doing, if it’s not inherently destructive to the profession, then live and let live. This goes out to the people who feel they need to “out” the haters, as well. Seriously folks we have enough people in the world who hate us – there’s no need to add to the already deafening noise.

Look, we all work 40-60 hours a week; many of us have families that include kids. Add in all the other peripheral daily nonsense, and it takes up a lot of our time. And we haven’t even included the amount of time spent at social recruiting events. Sometimes this is at a conference, and sometimes it’s just Wednesday. Where in the world do people find time to squeeze in extracurricular drama into their lives that eviscerates others? We shouldn’t have any spare time for this shit.

If you don’t believe that the vast majority of people in our field want to see all of us succeed, then maybe you need to check out #HROS – where sharing is caring is the message that is both preached and practiced.

Elie Wiesel spent his adult life trying to understand how human beings could be so horrible towards other people. He died this past weekend at the age of 87.

Wiesel was a Holocaust survivor whose post-concentration camp raison d’être was talking about his experiences as a then 15-year-old. With his passing comes a very simple declarative statement: Someone – or many – needs to take his place in seeking to understand why humans treat other humans so poorly because for certain, we haven’t progressed as far as we should.

While social media has its benefits, in reality for most it merely serves as a bully pulpit to exacerbate the nastiness and the worst that human beings can throw at each other. Trolls used to be mythical creatures and fairy tales; now they are educated professionals whose purpose in life appears to be foisting misery on others. Case in point with anti-Semite Max Blumenthal taking to Twitter to demonize Elie Wiesel after his death:

People troll over grammar; they troll over spelling; they troll over politics; they troll over religion; they troll over gender; they troll over the skin color of a President; they troll over a profession. They troll, troll, troll under the darkness of open social media platforms – because the platform gives them the tools and the emboldened voice to do so. There are anti-bullying groups on Facebook that get bullied and human resources and recruiting professionals who out of one side of the mouth claim compassion and on the other hand spew vitriol.

We say it is time to STOP the #noise. We have been spoken to via IM, Twitter, the book of Face, hell even on LI, and it is madness. People are wounded, hurt, and ashamed that friends are doing this yet they are silent. We three are not, and believe us, we did not want to write this, but we felt that we had to.

What we are saying is take a moment to breathe.

Think of what you are saying and how you are saying it.

Remember the Carpenter’s Maxim of Measure Twice, Cut Once before posting to social platforms.

Words can do more damage to a person’s soul than any beating that could be laid down and the scars can last a lifetime. For all involved…

Like this:

[originally published on ERE Media’s SourceCon site – link is at the end of this post]

Recruiting industry analyst Rob McIntosh believes “AI recruiting” is the future of recruiting. Ah, another future of recruiting article! Another tome in the latest assembly line of predictions that the profession will be elevated to the one where Supreme Bot Beings sit atop the Totem of Talent. Alas, being a human recruiter is no longer considered to be sexy enough for the Futurists.

Actually, automated recruiting isn’t what Rob is about, efficient recruiting is. We’ll get back to this notion in a few paragraphs.

It is very easy to be snookered in by the sweet smell of technology, unicorn valuations, 30 under 30 lists – and anything that comes to the masses via Google. But allow me to offer another perspective to this future of recruiting discussion.

Artificial Stupidity…

If there’s artificial intelligence, then by logic there has to be artificial stupidity – as in taking the Word of the Bot as Gospel. People, this is a very slippery slope that portends to push aside human expertise, experience, and compassion. Sure, the system can learn, the AlphaGo architecture is a unique extension of previous AI architectures (more about this soon), but humans have a funny way of turning logic on its side and playing a hunch that has a deeper, more robust meaning than any Monte Carlo tree search fueled by “…a huge amount of compute power” can make. Again, more about this later.

Just to be clear, I’m not against #BotRecruiting for the repeatable, scalable types of roles that take up so much of a Sourcer’s or Recruiter’s time, with or without pipelines and talent communities. Just the opposite, I’m very bullish on #AIrecruiting, addressing 68% of all hiring that isn’t significantly specialized (this is the plus or minus one standard deviation of all roles) based upon the range of problems to be solved when on the job.

I’m talking about large-scale hiring in, for instance, customer service, early career sales, retail, warehousing, even entry-level software development, where data is plenty, efficiency is a key goal, and humans are susceptible to injecting bias into the hiring process. I’m also bullish about an #AIrecruiting system that cultivates the digital crumbs and creates “probabilities of behavior” that can be used by human recruiters at some point in the process. We’re getting there tech-wise, but have a long way to move beyond black and white stones.

As promised earlier, one thing that Rob missed out on was describing AlphaGo’s architecture (it’s a darn good read), and why its performance is more evolved than previous attempts at building artificial intelligence solutions to games:

“…it combines a state-of-the-art tree search with two deep neural networks, each of which contains many layers with millions of neuron-like connections. One neural network, the “policy network”, predicts the next move, and is used to narrow the search to consider only the moves most likely to lead to a win. The other neural network, the “value network”, is then used to reduce the depth of the search tree — estimating the winner in each position in place of searching all the way to the end of the game.”

See what AlphaGo is doing with the parallel networks? Assessing hunches…feelings…ESP is what many recruiters call it. With experience, our hunches, fueled by many different scenarios and outcomes from the past, produce a higher probability of the likelihood of success, and with some hunches we learn that they don’t produce a desired outcome. Same with AlphaGo, as long as there’s more computing power to drive the parallel nature of the algorithm.

“Of course, all of this requires a huge amount of compute power, so we made extensive use of Google Cloud Platform, which enables researchers working on AI and Machine Learning to access elastic compute, storage and networking capacity on demand. In addition, new open source libraries for numerical computation using data flow graphs, such as TensorFlow, allow researchers to efficiently deploy the computation needed for deep learning algorithms across multiple CPUs or GPUs”

Let me put this another way: Remember the post-mortem analysis of meteorologists who had tried to predict the path of Hurricane Sandy? The picture below details all the models of possible paths based on a tremendous amount of data collected over decades. These models were created using a variety of simulations running on some of the most brutish computers on the planet. Yet we remember what happened, and the cost? Simulations and predictions are just that.

Each “Hurricane Sandy” adds more data and new sets of rules (learning) that enrich the model and change the hunches. Yet we all know that even the best model results in catastrophic damages. Sometimes the recruiting and hiring of the right person truly is a confluence of hunches, to an experienced recruiter, almost leaps of faith. This #AIrecruiting sure isn’t easy.

“One thing I’m seeing among my own faculty is the realization that we, technologists, computer scientists, engineers who are building AI, have to appeal to someone else to create these programs. When coming up with a driverless car, for example, how does the car decide what to do when an animal comes into the road? When you write the code there’s the question: How much is an animal’s life worth next to a human’s life? Is one human life worth the lives of a billion domestic cats? A million? A thousand? I would hate to be the person writing that code.”

Consider the #AIrecruiting software developer, if they are an avowed animal lover, do they play a Death Race 2000 scenario in their head while coding? This is one of many issues with developing systems to replace or augment humans.

Open source, open stack, and APIs too often mask the fact that there are human beings on the other side of the application. Artificial intelligence, machine learning, intelligence systems, and automation so good that they’ll replace human beings, are not by themselves the seeds of success but are foods that when consumed unchecked further the divide between people and technology. The carrot that is held in front of us, that will have more time to do the things we love, isn’t necessarily reality. Just like the addictiveness of drugs, alcohol, and cigarettes, technology draw us in and not let go. Ask me how often I’m hiking on a lonesome trail only to come across people glued to their smartphones.

More data does not mean necessarily translate into better decisions when the human brain is conditioned to trust the technology rather than the brain.

Perfect marriages end in divorce: what’s going to happen when all these perfect Bot selected people begin working with other perfect Bot selected people and one of them farts in a meeting? Or selects “Reply All” with an unfortunate joke? Or votes for Trump/Bernie/Clinton and posts it for the world to see? Or has sex with a co-worker on their desk, then breaks up with them the next week leading to a barrage of social media stupidity? Will the “person” who pushed these Bot hires through be dinged for a bad hire? Or will the #AIrecruiting system be forced to take a timeout?

Back to the use of AI in recruiting: the question to ask is what do we not do especially well right now? Let’s, as a profession, talk now about the rules that govern these tasks and continue to tune them until we reach consensus on best practices. Let’s decide upon where automation in recruiting makes sense for the people who are likely to be impacted by automation.

The journey from predicting the movement of black and white stones to the behavior of people replete with an unending number of human variables is a huge responsibility for our profession. Rather than get all worked up over a technology to replace people, think about how #AIrecruiting can serve to re-focus organizations on how important recruiting should be, to not only the solvency of companies but to the lives of the people we touch. It is the ethical thing for us to do.

Let’s end this tome with the last line of Aldous Huxley’s Brave New World – a fitting be careful what you wish for rejoinder to what happens when you implicitly trust technology:

“Slowly, very slowly, like two unhurried compass needles, the feet turned towards the right; north, north-east, east, south-east, south, south-south-west; then paused, and, after a few seconds, turned as unhurriedly back towards the left. South-south-west, south, south-east, east…”

Like this:

To recruiters who have never substantively sourced for people (sorry, but sending out InMauls one at a time or in quantities so large that a Bill of Lading is required, is not sourcing) – and to the hiring managers these recruiters support, Sourcing is not a spigot.

I know you asked for Sourcing’s assistance 24 hours ago but this doesn’t mean that we simply turn on a spigot and out comes a waterfall of people who want to interview with you.

Sourcing is the first date, perhaps days or weeks of missed texts and calls, unreturned emails, a second date, a hiking trip, several coffees – all before the extended foreplay begins. And perhaps more – although you never know…

Sourcing is typically called in after the misery of inbound Post & Pray activity produces a 90% or more rejection rate, driving the hiring manager to their boss who then calls up HR to complain. With Sourcing now “engaged”, Sourcing then asks for an intake meeting (the one that really should have been held in the first place) with the recruiter and the hiring manager to procure the information needed to get down and dirty into the lairs where the Golden Children live. You know what info I’m alluding to – forums, newsletters, websites, associations, conferences, ad infinitum. We use these as jumping off points into the nooks and crannies of people’s lives in search of their digital crumbs that when mixed together with a soupçon of badass engagement produces conversations – first dates.

“Another meeting?” exasperates the hiring manager. “Everything you need is in the job description.” Of course that is simply untrue.

[actually sourcing happens in secret even before the sourcing, recruiting, hiring manager hook-up but this for another post]

Sourcing intake makes everyday recruiting intake look like child’s play. Sourcers are like Michelangelo’s Creation of Adam – reaching out to people they do not know so there’s special knowledge that’s required to instigate the outreach.

We’re Sourcers, Purveyors of the Spigot and Waterfall. So we source. And 24 hours go by and no one has been sent to the recruiter! The resultant exclamation from the hiring manager, “What are we paying you people for?” stings like slap to a fresh sunburn. At the end of this chain of command, Sourcing often finds itself at the ugly end of a snide remark uttered by a recruiter. Failures.

Like Hell we are.

Sourcing doesn’t exist to make recruiting look good – nor are Sourcers subservient to Recruiters (see previous paragraph and extrapolate from “snide remark”). I could toss in the word Partners but that implies the presence of a Service Level Agreement that places sourced people and employee referrals in the same category. Frankly, I believe Sourcing serves at the pleasure of the CEO – think of it as Sourcing Team 6 – to identify people and competitive intelligence that enable the organization’s driver to make split-second changes to road map.

Like this:

Boston-area analytics looking to bring on a few more devs to work on the various short and future projects – some of the details are below (any more detail requires a signed NDA or the possibility of death). Roles are senior to team lead – both have architecture elements; openings are because of life changes for folks who have moved on, for people who have been promoted, and for adding to the teams as a result of both new business and for customers requiring substantially more functionality.

The head of software technology is pretty darn easy-going and is a Luke Starwalker wannabe who keeps a light saber handy (but seems to always be in need of new batteries). The company began as a startup, grew, made money, yet retains some startup feel to it (just like adults have the knack for acting like goofy kids when needed). You don’t have to be in the office all the time and if you wear business casual you will likely be met with multiple Golden Retriever head-tilts.

So read on – and LMK what resonates with you (my email is at the bottom). No résumé is needed because we’re just talking…

Details About The Pipeline

Pipeline processing utilizes Torque (batch server) and Hadoop

Data needed for processing are stored in MySQL and Vertica databases

Vertica is used for generating reports used by Data Quality and Data Acquisition; pipeline jobs are orchestrated by a proprietary interface built on top of Luigi; ad-hoc access to pipeline files in HDFS is provided via Hive

Initial prep of pipeline files, such as cleansing and removal of sensitive data is via Python scripts and C++ compiled programs; the bulk of the rest of the processing is implemented as Python scripts and Map/Reduce jobs in Hadoop using streaming interface

The Company’s Development Approach

Agile and Scrum with 3 weeks Sprints with emphasis on high priority stories (typically 80+% acceptance of stories)

Rally project management

No special support bucket

Scrum and tickets for DevOps

The Software Development Flow

GIT for source control; repos are hosted internally

Gerrit for code reviews and merges (developer pushes changes in their topic branch up for review)

Jenkins for deployment and unit tests (kicks off master merge to Gerrit)